1. Field of the Invention
The present invention relates to a mobile portable terminal, communication host apparatus, and weather forecasting system, and more particularly to a mobile portable terminal that can implement weather forecasting, a communication host apparatus for causing weather forecasting to be implemented by this mobile portable terminal, and a weather forecasting system that includes a mobile portable terminal and communication host apparatus.
2. Description of the Related Art
In prior art literature 1 through 6 cited below, inventions are proposed that enable weather forecasting to be implemented using a mobile portable terminal. In literature 1 (Unexamined Japanese Patent Publication No. 2000-155178), a method is proposed whereby weather is forecast from measurement information obtained from a plurality of kinds of weather satellites, the location of a mobile portable terminal incorporating a GPS (Global Positioning System) function is identified using GPS, the weather of a localized area a short time later is forecast, and is distributed to the mobile portable terminal.
In literature 2 (Japanese Patent Publication No. 3366275), a method is proposed whereby a weather sensor is installed in a PHS channel base station, a user makes a request to a weather information center from a fixed telephone, the weather information center collects local weather information using the weather sensor installed in the base station, and provides this information to the user.
In literature 3 (Unexamined Japanese Patent Publication No. 2001-136568), literature 4 (Unexamined Japanese Patent Publication No. 2002-044289), and literature 5 (Unexamined Japanese Patent Publication No. 2002-148061), methods are proposed whereby a mobile communication network is used, weather sensors are installed in mobile portable terminals, and information obtained by these weather sensors is collected and used for weather forecasting.
Details of a method whereby weather forecasting is performed based on obtained weather information (temperature, humidity, barometric pressure, sunshine, precipitation, cloud formation, wind speed, and wind direction) are given in literature 6 (NHK Broadcasting Culture Research Institute, “NHK Weather Handbook Revised Version,” October 1996, Japan Broadcasting Publishing Corporation).
Using a mobile communication network, installing weather sensors in mobile portable terminals, collection information obtained by the weather sensors, and performing weather prediction using that information to predict the weather is an effective method for making a weather forecast for a short period of no more than several hours (hereinafter referred to as a “nowcast”). Since sudden rain is a serious problem for street vendors and companies involved in organizing outdoor events, for example, and sudden localized torrential rain may cause major damage, accurate nowcasts are vitally important. However, accurate nowcasts are often very difficult to achieve, as explained below.
At present, nowcasts made by the Meteorological Office are within a range of one to six hours or so. For example, a current precipitation nowcast predicts the hourly amount of precipitation up to six hours in advance. For nowcasts, a method is used in which two methods—a numerical forecasting model and running extrapolated prediction—are combined after deciding on their respective weightings.
In a numerical forecasting model, a meso-value forecasting model is used that makes a meso-scale phenomenon forecast for several hours in which the horizontal scale is in a range of several tens of kilometers to several hundred kilometers or so. A meso-value forecasting model actually uses weather information automatically observed in a regional weather observation system in which one location is set up in an approximately 20 km square area (hereinafter referred to by its popular name “AMEDAS”). Running extrapolated prediction predicts the amount of rainfall several hours later from the amount of rainfall of a 2.5 km square area found from the radar AMEDAS analysis amount of rainfall.
AMEDAS information used in a numerical forecasting model is for one location in a 20 km square area, and information for a smaller region than this cannot be observed. Also, for the radar AMEDAS analysis amount of rainfall used in running extrapolated prediction, the amount of rainfall in a 2.5 km square area is found, but since the measured value is affected by the terrain and so forth, accuracy is poorer than for the AMEDAS amount of rainfall.
Thus, in actuality, radar AMEDAS analysis rainfall and AMEDAS rainfall are used in a numerical forecasting model while being compared and corrected. Also, while a prediction after a time elapse can be found by extrapolation of estimated values, the amount of precipitation that occurs from the initial time onward cannot be predicted.
In nowcasts, since time and space scales are often small and meteorological phenomena fluctuate violently, and weather information for a range smaller than the AMEDAS range cannot be observed accurately, in many cases weather forecasts cannot be made accurately. For these reasons, in particular, it is currently difficult to make a weather forecast for an extremely short period, such as within an hour, for example.
In a radio mobile communication system, the cell radius of a base station is in a range of several hundred meters to several kilometers, and in the case of a cell radius of several kilometers, a single cell is often divided into a plurality of sectors. That is to say, a radio mobile communication system can collect weather information for areas smaller than the installation zones of AMEDAS.
If GPS, which is expected to become increasingly widespread in the future, is installed in a mobile portable terminal, more precise positioning is made possible. That is to say, if a weather sensor is installed in each mobile portable terminal, a mobile communication network is used, and weather sensor information is collected, weather information for much smaller areas than with AMEDAS can be collected at short time intervals, and it possible to make accurate nowcasts.
However, in the case of the inventions disclosed in above-mentioned literature 1 through 5, concretized contents for collecting weather information and performing nowcasts are not described in practical terms, and as of now these inventions have not been put into actual use. In order to collect weather information and implement nowcasts, it is necessary to solve the following kinds of problems.
The first problem is that, when weather information is collected by a mobile portable terminal, fewer kinds of weather information can be acquired. Normally, it is necessary for weather information used for weather forecasting to include barometric pressure, temperature, wind direction, wind speed, precipitation, humidity, duration of sunshine, amount of solar radiation, cloud formation, and so forth, and these items of weather information are observed automatically by means of measuring devices. On the other hand, when small size and low cost are taken into consideration, weather sensors that can actually be installed in a mobile portable terminal are probably weather sensors capable of measuring temperature, humidity, barometric pressure, and sunshine, and such sensors cannot, of course, measure weather information other than temperature, humidity, barometric pressure, and sunshine—that is to say, wind direction, wind speed, precipitation, and cloud formation.
The second problem is that the reliability of weather information observed by weather sensors installed in a mobile portable terminal is lower than that of weather information observed by means of AMEDAS. A mobile portable terminal is required to be small and low-priced, and it is difficult to include expensive, high-precision weather sensors. Moreover, observations by weather sensors may be made under various conditions, such as when a mobile portable terminal is inside a bag or case, when a mobile portable terminal is left in an air-conditioned room, and when a mobile portable terminal is carried on the person and is affected by body temperature. It will probably continue to be difficult to incorporate expensive, high-precision weather sensors in mobile portable terminals in the future, and an important consideration is how accurate the weather information collected by the weather sensors can be made—that is, how efficiently weather information that is not necessary for weather forecasting can be eliminated from the collected weather information.
The third problem is that it is difficult to transmit large quantities of weather information data using a mobile portable terminal. In a normal mobile communication network, packet communication is used for non-voice communication, and a billing system is used in which charges depend on the amount of information transmitted and received. Taking factors such as reducing communication charges and decreasing communication traffic into consideration, it is desirable for the amount of measured weather information data transmitted to be kept as small as possible.
If the frequency of communication of a mobile portable terminal is reduced and the communication time interval is increased, both communication charges and communication traffic can be reduced. With AMEDAS, weather observations are made once every 10 minutes. However, in mobile communications, making weather observations once every 10 minutes and transmitting weather information regularly each time represents a comparatively high frequency of transmission. Also, as described above, transmitting weather information regularly at short time intervals is necessary in order to make accurate weather forecasts at short intervals for a small area.
The fourth problem is that it is difficult to execute complex computational processing and large-volume information processing based on weather information in a mobile portable terminal. Although mobile portable terminals have achieved major advances in terms of functionality and processing performance, there is still a strong demand for lighter weight and lower power consumption. It is desirable for a mobile portable terminal to execute simple computational processing and small-volume information processing based on weather information.
The fifth problem, specific to mobile communications, is that the location of a mobile portable terminal changes frequently. For example, to consider a case where the user of a mobile portable terminal receives weather information in that mobile portable terminal while moving at high speed, it is necessary to consider how to provide accurate weather information in the area in which the user is currently located.